title: A metabonomic approach applied to predict patients with cerebral infarction.
abstract: Cerebral infarction is always of sudden onset, and usually leading to serious consequence. It is of therapeutic significance to develop fast and accurate diagnosis methods for cerebral infarction so that patients can be treated timely and properly. A metabonomic approach was then proposed to investigate the potential biomarkers and metabolic pathways associated with cerebral infarction and also establish a prediction model of cerebral infarction for the fast diagnosis. Serum metabolic profiling of sixty-seven cerebral infarction patients and sixty-two controls was obtained using UPLC-TOF MS. The resulting data were then processed by multivariate statistical analysis to graphically demonstrate metabolic variations. The PLS-DA model was validated with cross validation and permutation tests to assure the model's reliability, and significant difference was obtained between the original and hypothetical models (p<0.0001). A series of endogenous metabolites in the one-carbon cycle, such as folic acid, cysteine, S-adenosyl homocysteine and oxidized glutathione, were determined as potential biomarkers of cerebral infarction. A prediction model developed using PLS-KNN algorithm was established to differentiate cerebral infarction patients from controls, and an average accuracy of 100% was obtained. In conclusion, metabonomic approach is a powerful tool to investigate the pathogenesis of stroke and is expected to be developed as a useful method for the fast diagnosis.
authors.affiliation: School of Pharmacy, East-China University of Science & Technology, Shanghai, PR China.
authors.forename: Zhiting
authors.initials: Z
authors.lastname: Jiang
authors.forename: Jingbo
authors.initials: J
authors.lastname: Sun
authors.forename: Qionglin
authors.initials: Q
authors.lastname: Liang
authors.forename: Yefeng
authors.initials: Y
authors.lastname: Cai
authors.forename: Shasha
authors.initials: S
authors.lastname: Li
authors.forename: Yan
authors.initials: Y
authors.lastname: Huang
authors.forename: Yiming
authors.initials: Y
authors.lastname: Wang
authors.forename: Guoan
authors.initials: G
authors.lastname: Luo
mesh_terms: D000368:Aged; D015415:Biomarkers / Q000032:analysis*; D016022:Case-Control Studies; D002544:Cerebral Infarction / Q000175:diagnosis*; D002853:Chromatography, Liquid; D005260:Female; D006801:Humans; D008297:Male; D013058:Mass Spectrometry; D055432:Metabolomics; D008875:Middle Aged
chemical_list: D015415:Biomarkers